This paper presents our work on textual inference and situates it within the context of the larger goals of machine reading. The textual inference task is to determine if the meaning of one text can be inferred from the meaning of another and from background knowledge. Our system generates semantic graphs as a representation of the meaning of a text. This paper presents new results for aligning...

The domains of data mining and knowledge discovery make use of large amounts of textual data, which need to be handled efficiently. Specific problems, like finding the maximum weight ordered common subset of a set of ordered sets or searching for specific patterns within texts, occur frequently in this context. In this paper we present several novel and practical algorithmic techniques for proc...

The CORAS method for security risk analysis provides a customized language, the CORAS diagrams, for threat and risk modelling. In this paper, we extend this language to capture context dependencies, and use it as a means to analyse mutual dependency. We refer to the extension as dependent CORAS diagrams. We de ne a textual syntax using EBNF and explain how a dependent CORAS diagram may be schem...

Multimedia content can be described at different levels of abstraction such as measures of video colour, texture and motion and comparatively high-level 'semantic' descriptions in textual form. The textual description of moving images at different levels of abstraction can be explored in the context of moving images from a specialist domain, such as sequences of dance. The KAB system annotates ...

DEFINITION The widespread search engines, in the professional as well as the personal context, used to work on the basis of textual information associated or extracted from indexed documents. Nowadays, most of the exchanged or stored documents have multimedia content. To reduce the technological gap so that these engines still can work on multimedia content, it is very convenient developing met...

The adoption of mobile devices is pushing the Internet into a more personal and context aware space. A common challenge for online news services is to deliver contents that are interesting to read. In this paper, we describe the user interface design of the SmartMedia news recommender prototype. Through deep analysis of textual news contents it is able to deliver local, recent and personalized ...

In this poster, we present the actual state of our work on the possible derivation of ontological structures from textual analysis. We propose an approach to the extension of existing domain ontologies or even to the semi-automatic ontology generation of such ontologies from scratch, on the base of heuristic rules applied to the result of a multi-layered processing of textual documents. This on...

This year we participated in the English monolingual paragraph selection task at ResPubliQA 2010. Our general strategy is to find the supporting word context from query and candidate passages during the paragraph selection. We use the techniques of state-of-the art publicly available question answering systems, i.e. Open Ephyra and JIRS, and the random projection implementation in the Semantic ...

Semantic Textual Similarity measures similarity between pair of texts, even though the similar context is projected using different words. This work attempted to incorporate the context space of the sentence from that sentence alone. It proposes combination of Word2Vec and Non-Negative Matrix Factorization to represent the sentence as context embedding vector in context space. Distance and corr...

Business Process (BP) improvement and alike require accurate descriptions of the BPs. We suggest to describe BPs as use case specifications. A use case specification comprises a description of the context of the BP, the interactions between the agents involved in the BP, the interactions of these agents with an automated system supporting the BP and attached system internal requirements. Constr...